3 papers
cond-mat.dis-nn2026
Do Hopfield Networks Dream of Stored Patterns? A Statistical-Mechanical Theory of Dreaming in Multidirectional Associative Memories
Adriano Barra, Fabrizio Durante, Andrea Ladiana +1
We introduce the Dreaming -directional Associative Memory (DLAM), a multi-layer Hebbian architecture in which off-line dreaming and supervised heteroassociative coupling coexist…
cond-mat.dis-nn2026
A Federated Many-to-One Hopfield model for associative Neural Networks
Andrea Alessandrelli, Fabrizio Durante, Andrea Ladiana +1
Federated learning enables collaborative training without sharing raw data, but struggles under client heterogeneity and streaming distribution shifts, where drift and novel data c…
cond-mat.dis-nn2024
Hebbian Learning from First Principles
Linda Albanese, Adriano Barra, Pierluigi Bianco +2
Recently, the original storage prescription for the Hopfield model of neural networks -- as well as for its dense generalizations -- has been turned into a genuine Hebbian learning…